class_docstr: Computing filter banks is applying triangular filters on a Mel-scale to the power
   spectrum to extract frequency bands. Return a float tensor with shape
   (num_channels, num_frames, num_frequencies).
code: def __init__(self, config: dict):
      super().__init__(config)
      self.spect = Spectrum(config)
  
file_path: delta/delta/data/frontend/fbank.py
imports: import tensorflow
  from core.ops import py_x_ops
  from delta.utils.hparam import HParams
  from delta.data.frontend.base_frontend import BaseFrontend
  from delta.data.frontend.spectrum import Spectrum
label_desc: Use image node_id 1 to create a new Fbank object from inherited base classes: BaseFrontend with example: obj = Fbank(config)